Utilizing an Automated SERS-Digital Microfluidic System for High-Throughput Detection of Explosives.

Abstract

The surface-enhanced Raman scattering (SERS) technique is a promising method for the detection of explosives such as 2,4,6-trinitrotoluene (TNT) and 3-nitro-1,2,4-triazol-5-one (NTO) because of its high sensitivity to trace substances. However, most SERS detection processes are often nonautomated as well as exhibit low efficiency and toxic exposure, which often poses potential danger to operators. Herein, we propose the integration of SERS with digital microfluidics (SERS-DMF) for automated, high-throughput, and high-sensitivity detection of explosives. First, we carefully designed a DMF chip comprising 40 drive electrodes and 8 storage electrodes to achieve a high-throughput process. And different concentrations of target molecules, silver nanoparticles (Ag NPs), and salts were loaded into the DMF chip. Then, the droplet aggregation, incubation, and detection processes were automatically controlled using the SERS-DMF platform. In addition, Ag NPs were efficiently aggregated by screening different types and concentrations of salts, resulting in "hotspots" and the SERS effect. With the help of the SERS-DMF platform, two explosive samples were automatically detected with high throughput and high sensitivity. The detection limits of TNT and NTO were 10-7 and 10-8 M, respectively. In addition, compared with nonautomatic operations, the SERS-DMF platform exhibited better reproducibility and higher efficiency for the detection of explosives. The proposed SERS-DMF thus has considerable potential as an analytical technique for detecting hazardous substances.